Scientific Data · 2018 · 118 citations · 42 references
ComputingGeographyGeoinformaticsGeographic Information SystemsRemote SensingSpatial AnalysisLand Cover ClassificationLand Cover MappingLand UseLand Use Change DetectionLand-use ChangeRemote Sensing Change DetectionAbandonmentAgricultural AbandonmentAgricultural Land AbandonmentLand Use MappingLand Use ModelingMap Accuracy AssessmentMap Interpretation AccuracyTemporal Land Use Mapping
The spatial distribution of agricultural abandonment after the Soviet Union’s collapse is poorly understood. The study aims to produce a high‑resolution (10″) map of arable and abandoned land for 2010 across the former Soviet Union. The authors fused multi‑scale land‑cover and land‑use maps using visual interpretation of very‑high‑resolution imagery as training data, and validated the product with an independent dataset. The resulting map achieves regional accuracies ranging from 78 % to 95 % and can support biogeochemical, land‑use, and ecosystem‑services modelling.
Abstract Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery. We have also collected an independent validation data set to assess the map accuracy. The overall accuracies of the map by region and country, i.e. Caucasus, Belarus, Kazakhstan, Republic of Moldova, Russian Federation and Ukraine, are 90±2%, 84±2%, 92±1%, 78±3%, 95±1%, 83±2%, respectively. This new product can be used for numerous applications including the modelling of biogeochemical cycles, land-use modelling, the assessment of trade-offs between ecosystem services and land-use potentials (e.g., agricultural production), among others.
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